Mini-Course Description:
M215: Applied Statistical Analysis with Mathematica

Course Objective
This mini-course series is designed to give experience with the statistical tools that are available in Mathematica. Using real-world and simulated data sets, participants will import data, extract parts of the data based on various criteria sets, analyze the data, and visualize the results.

Presenter
The course is presented by a Wolfram Research senior developer or a Wolfram Education Group certified instructor.

Target Audience
The course is designed for people who work with data and wish to improve their skills at using Mathematica for performing statistical analyses of data. Typical attendees include engineers, physicists, analysts in finance, and those in the physical sciences and the life and medical sciences.

Delivery Type
The online mini-course series consists of two independent sections: M215A and M215B. Each section is three to four hours long. Attendees may take one or both of these sections in whichever order they wish. The M215A/B course combines the two sections into one full day of training and is offered in computer classroom facilities.

Syllabus

M215A: Applied Statistical Analysis with Mathematica: Descriptive and Mathematical Statistics

• Computing basic descriptive statistics of data (mean, median, variance, etc.)
• Visualizing statistical data (including box plots, scatter plots, and histograms)
• Computing and visualizing properties of continuous and discrete distributions, such as mean, PDF, CDF, expectations, and quantiles
• Random number generation from continuous and discrete distributions
• Hypothesis testing (including t-tests, z-tests, and chi-squared tests) and confidence intervals
• Analysis of variance (ANOVA)

M215B: Applied Statistical Analysis with Mathematica: Regression

• Curve fitting via ordinary least squares, alternative metrics, and merit functions
• Linear and nonlinear regression
• Obtaining and visualizing regression diagnostics
• Data transformations
• Robust regression via iterative reweighting
• Maximum likelihood estimation
• Fitting generalized linear models

Course Materials
Each attendee will be provided with Mathematica course notebooks and access to the current version of Mathematica. The course notebooks require Mathematica or Mathematica Player. For attendees participating in classroom-based sessions, course materials are distributed in print and on CD-ROM, and are yours to keep; a computer running Mathematica is available for your use during class. For attendees participating in online classes, a download of the course materials is provided; a temporary Mathematica training license is provided upon request.

Prerequisites
Course attendees are expected to have basic familiarity with Mathematica approximately equivalent to that provided by "M101: A First Course in Mathematica." Attendees should also have basic knowledge of descriptive statistics, mathematical statistics (to a lesser extent), hypothesis testing, ANOVA, and regression.

To sign up for this course, see the training calendar and registration page.